Charting

Follow these steps to import the libraries that you need:

1. Load the assembly files and data types in their own cell.

#load "../Initialize.csx"

2. Load the necessary assembly files.

#load "../QuantConnect.csx"
#r "../Plotly.NET.dll"
#r "../Plotly.NET.Interactive.dll"

3. Import the QuantConnect, Plotly.NET, and Accord packages.

using QuantConnect;
using QuantConnect.Research;
            
using Plotly.NET;
using Plotly.NET.Interactive;
using Plotly.NET.LayoutObjects;
            
using Accord.Math;
using Accord.Statistics;

Get some historical market data to produce the plots. For example, to get data for a bank sector ETF and some banking companies over 2021, run:

var qb = new QuantBook();
var tickers = new[] 
{
    "XLF",  // Financial Select Sector SPDR Fund
    "COF",  // Capital One Financial Corporation
    "GS",   // Goldman Sachs Group, Inc.
    "JPM",  // J P Morgan Chase & Co
    "WFC"   // Wells Fargo & Company   
};
var symbols = tickers.Select(ticker => qb.AddEquity(ticker, Resolution.Daily).Symbol);
var history = qb.History(symbols, new DateTime(2021, 1, 1), new DateTime(2022, 1, 1));

You must import the plotting libraries and get some historical data to create candlestick charts.

In this example, you create a candlestick chart that shows the open, high, low, and close prices of one of the banking securities. Follow these steps to create the candlestick chart:

1. Select a Symbol.

var symbol = symbols.First();

2. Call the Chart2D.Chart.Candlestick constructor with the time and open, high, low, and close price IEnumerable.

var bars = history.Select(slice => slice.Bars[symbol]);
var chart = Chart2D.Chart.Candlestick<decimal, decimal, decimal, decimal, DateTime, string>(
    bars.Select(x => x.Open),
    bars.Select(x => x.High),
    bars.Select(x => x.Low),
    bars.Select(x => x.Close),
    bars.Select(x => x.EndTime)
);

3. Call the Layout constructor and set the title, xaxis, and yaxis properties as the title and axes label objects.
   

LinearAxis xAxis = new LinearAxis();
xAxis.SetValue("title", "Time");
LinearAxis yAxis = new LinearAxis();
yAxis.SetValue("title", "Price ($)");
Title title = Title.init($"{symbol} OHLC");

Layout layout = new Layout();
layout.SetValue("xaxis", xAxis);
layout.SetValue("yaxis", yAxis);
layout.SetValue("title", title);

4. Assign the Layout to the chart.
   

chart.WithLayout(layout);

5. Show the plot.
   

HTML(GenericChart.toChartHTML(chart));

The Jupyter Notebook displays the candlestick chart.

You must import the plotting libraries and get some historical data to create line charts.

In this example, you create a line chart that shows the volume of a security. Follow these steps to create the chart:

1. Select a Symbol.

var symbol = symbols.First();

2. Call the Chart2D.Chart.Line constructor with the timestamps and volumes.

var bars = history.Select(slice => slice.Bars[symbol]);
var chart = Chart2D.Chart.Line<DateTime, decimal, string>(
    bars.Select(x => x.EndTime),
    bars.Select(x => x.Volume)
);

3. Create a Layout.
   

LinearAxis xAxis = new LinearAxis();
xAxis.SetValue("title", "Time");
LinearAxis yAxis = new LinearAxis();
yAxis.SetValue("title", "Volume");
Title title = Title.init($"{symbol} Volume");

Layout layout = new Layout();
layout.SetValue("xaxis", xAxis);
layout.SetValue("yaxis", yAxis);
layout.SetValue("title", title);

4. Assign the Layout to the chart.
   

chart.WithLayout(layout);

5. Show the plot.

HTML(GenericChart.toChartHTML(chart));

The Jupyter Notebook displays the line chart.

You must import the plotting libraries and get some historical data to create scatter plots.

In this example, you create a scatter plot that shows the relationship between the daily price of two securities. Follow these steps to create the scatter plot:

1. Select two Symbol objects.

var symbol1 = symbols.First();
var symbol2 = symbols.Last();

2. Call the Chart2D.Chart.Point constructor with the closing prices of both securities.

var chart = Chart2D.Chart.Point<decimal, decimal, string>(
    history.Select(slice => slice.Bars[symbol1].Close),
    history.Select(slice => slice.Bars[symbol2].Close)
);

3. Create a Layout.
   

LinearAxis xAxis = new LinearAxis();
xAxis.SetValue("title", $"{symbol1} Price ($)");
LinearAxis yAxis = new LinearAxis();
yAxis.SetValue("title", $"{symbol2} Price ($)");
Title title = Title.init($"{symbol1} vs {symbol2}");

Layout layout = new Layout();
layout.SetValue("xaxis", xAxis);
layout.SetValue("yaxis", yAxis);
layout.SetValue("title", title);

4. Assign the Layout to the chart.
   

chart.WithLayout(layout);

5. Show the plot.

HTML(GenericChart.toChartHTML(chart));

The Jupyter Notebook displays the scatter plot.

You must import the plotting libraries and get some historical data to create heat maps.

In this example, you create a heat map that shows the correlation between the daily returns of the banking securities. Follow these steps to create the heat map:

1. Compute the daily returns.

var data = history.SelectMany(x => x.Bars.Values)
    .GroupBy(x => x.Symbol)
    .Select(x =>
    {
        var prices = x.Select(x => (double)x.Close).ToArray();
        return Enumerable.Range(0, prices.Length - 1)
            .Select(i => prices[i+1] / prices[i] - 1).ToArray();
    }).ToArray().Transpose();

2. Call the Measures.Correlation method.

var corrMatrix = Measures.Correlation(data).Select(x => x.ToList()).ToList();

3. Call the Plotly.NET.Chart2D.Chart.Heatmap constructor with the correlation matrix.

var X = Enumerable.Range(0, tickers.Length).ToList();

var heatmap = Plotly.NET.Chart2D.Chart.Heatmap<IEnumerable<double>, double, int, int, string>( 
    zData: corr,
    X: X,
    Y: X,
    ShowScale: true,
    ReverseYAxis: true
);

4. Create a Layout.
   

var axis = new LinearAxis();
axis.SetValue("tickvals", X);
axis.SetValue("ticktext", tickers);
            
var layout = new Layout();
layout.SetValue("xaxis", axis);
layout.SetValue("yaxis", axis);
layout.SetValue("title", Title.init("Banking Stocks and bank sector ETF Correlation Heat Map"));

5. Assign the Layout to the chart.
   

heatmap.WithLayout(layout);

6. Show the plot.

HTML(GenericChart.toChartHTML(heatmap))

The Jupyter Notebook displays the heat map.